Mission Control: Breaking down the FDA’s request
In its July 2015 draft the FDA described its “Goals for FDA’s application of Quality Metrics,” which include developing objective measures for drug product and site quality and the effectiveness of systems associated with manufacturing. The FDA wants to “Conduct continual monitoring, assessment, and reporting on the state of quality across the inventory of drug products and facilities regulated by FDA,” noting it “Can only be as good as the quality of available data and analytic tools.”1
In a new era of manufacturing collaboration and outsourcing, it’s reasonable to say that the FDA really wants to boost public confidence in the manufacturing quality solar system as a whole—lining up with its 21st century vision for quality. It doesn’t care whether data comes from Venus, Mars, Jupiter or its many moons. Its inspectors just need reliable proof that everyone is in a safe orbit around the sun in lockstep to benefit the public.
The data-driven reporting system proposed in the quality metrics draft guidance will help the FDA better assess risks to prioritize its inspections. The FDA specifies in its draft who will do the reporting, asking for one report for each drug. To deliver, sponsors will need to combine quality data from all contractors in one report.
The draft guidance says, “FDA believes that, as part of its responsibility for oversight and controls over the manufacture of drugs to ensure quality, one establishment will already possess or have access to all of the quality metrics data needed to submit such reports, for example, through contract, this establishment should combine the data so that a single report is submitted for each FDF and each API.”1
Manufacturers who already have more sophisticated quality metrics in place are setting examples for how the rest of the industry can comply. In their sponsor/contractor relationships they’re already sharing responsibility for quality, so we can learn from their best practices.
The Mission for Mars: Sponsors’ story
As the “reporting establishment” tasked with delivering metrics to comply with FDA’s quality reporting requests, sponsors need to incorporate quality data from disparate systems, including from contractors who could be located around the globe. They’re likely already gathering data from their own internal initiatives, such as continuous process verification (CPV), but adding data from CMOs—each with their own systems and sources—can be a numbers nightmare.
So how do parties enable practical quality metrics data sharing? Exemplary sponsors have learned from establishing contractor agreements over time that details must be spelled out from the start or added as addenda to contracts later. They can’t just assume data sharing will happen without plans in place that assign roles and tasks, similar to the way they manage most internal projects by delineating responsibilities between manufacturing, quality and development departments, for example.
Since quality is a shared responsibility and CMOs are considered extensions of the product owners’ own operations, they have to make quality metrics a mandatory component of contractor’s evaluation. Using the FDA’s proposed quality metrics offers a template to build upon.
- Lot Acceptance Rate = 1 – x (x = the number of specification-related rejected lots in a timeframe divided by the number of lots attempted by the same establishment in the same timeframe).
- Product Quality Complaint Rate = the number of product quality complaints received for the product divided by the total number of lots of the product released in the same timeframe.
- Invalidated Out-of-Specification (OOS) Rate = the number of OOS19 test results for the finished product invalidated by the establishment divided by the total number of OOS test results divided by the total number of tests performed by the establishment in the same timeframe.
- Annual Product Review (APR) or Product Quality Review (PQR) on Time Rate = the number of APRs or PQRs completed within 30 days of annual due date at the establishment divided by the number of products produced at the establishment.1
Enabling data sharing across sites at all stages of process development and manufacturing is paramount to quality metrics management. Using technology to automatically gather the right information and deliver the data analysis needed to support an APR, for example, can save valuable days and weeks for each product. Without automation, many human hours are spent manually collecting and analyzing data from disparate systems and contractors, so technology frees up staff time to work on other activities and greatly reduces the potential for errors. Cost benefits and assurance that contractors are in line with expectations help investments payoff more quickly.
In its 2016 Global Life Sciences Outlook Report, Deloitte cites outdated IT infrastructure as a focus for countering industry pricing and cost pressures. It says, “Many life sciences companies are spending considerable sums to fix operational and compliance issues caused by an outdated IT infrastructure. For example, an infrastructure designed around an impermeable core may hamper external collaboration, an important element of open innovation in R&D. From a compliance perspective, outdated IT systems may stymie efforts to meet mandatory FDA GxP requirements for pharma manufacturing and product quality.”2
With updated technology in place sponsors’ CPV programs can include contractors to help organize thousands of parameter values that can be used for improving upon monitored processes. Sponsors who are just starting a monitoring program will gain better overall understanding of their processes and products, enabling global data-driven decision-making, such as where to invest in improvements. Having consistent quality metrics in place for review ensures multiple CMOs are following the same best practices.
The View from Venus: Contractors’ perspective
On the other side of the manufacturing galaxy, what’s being asked of contract manufacturers? And how can they be prepared to address the four quality metrics to comply with FDA’s and their sponsor customers’ requirements?
In its Contractor Quality Guidance, the FDA explains that CMOs are considered extensions of the product owner, with liability falling on the sponsor. While they don’t carry the burden associated with report ownership, to stay competitive they must provide sponsors with the required data.
Clarkston Consulting’s 2016 report on Contract Manufacturing Industry Trends, outlines the top worries for life sciences CMOs, including focusing on customer service. It says, “With tight profit margins and strained resources, some CMOs are struggling with how to best serve their customers. Large scale changes that improve customer service requires CMOs to invest in new areas, such as project management, contract development and execution, enterprise technology, capacity management and quality.”3
Improving customer service for multiple sponsor customers with diverse requirements is a cumbersome task, due to the large volume of process data generated. For just one sponsor, a CMO might run only a handful of product batches—a small portion of the CMO’s volume, but critical to the sponsor and its end consumers.
Installing a secure, central, collaborative data management and access system for process monitoring and analysis across all sponsors can maximize the CMO’s return on investment and minimize its staff time requirements, while minimizing the risks of errors. Organizing quality data around the FDA’s four recommended metrics actually simplifies the work for CMOs. Those who already do this see a competitive advantage, because sponsors have an easier time evaluating results. CMOs can demonstrate lot acceptance rates and OOS rates, for example, to show process improvements in line with on time product delivery.
Reporting efforts can ultimately encourage a culture of quality for CMOs, but IT systems are also needed to automate these areas:
- Transforming paper records from manufacturing processes into compliant electronic records readily available for analysis;
- Employing tools to aggregate and contextualize data from disparate systems (e.g.,LIMS, CAPA) and a common collaborative technology platform for improving process understanding; and
- Providing secure access to data for specific sponsors, while excluding access to other sponsors’ confidential data.
As an added benefit, the CMO can leverage hierarchies for its own process improvements and to meet its sponsors’ requirements for secure real-time access to quality data. Shared hierarchies provide foundations for analysis and reporting—from raw materials and process analysis to process outcome trending, comparisons, and investigations for process understanding. Typically, the shared data resides on secure servers at the CMO or sponsor site, and the shared hierarchies sit behind firewalls that control access to authorized sponsors and CMOs.
CMOs can rally around shared goals with sponsors, including reduced potential for disruptive, protracted regulatory inspections, along with significant potential business benefits. They can share manufacturing process and quality data in real time internally, and with sponsors externally, to perform proactive monitoring and investigative analysis collaboratively for better process understanding and control of variability.
To Infinity and beyond: Embracing optional quality metrics
The FDA invited comments about three optional quality metrics related to quality culture and process capability/performance. Each of these has the potential to benefit both sponsors’ and contract manufacturers’ businesses, as well as demonstrating “evidence of manufacturing robustness and a commitment to quality.” The FDA’s says, “Data from these optional metrics may merit a reduction in inspection frequency.”
It acknowledges the importance of “quality culture to the overall state of quality of the product, process, and commitment to quality,” saying, “We also recognize that many companies measure quality culture and encourage this practice.”
Related to quality culture, FDA suggests these metrics:
- Senior management engagement, saying, “A corporate commitment to quality has been identified in multiple public forums as a strong indicator of a robust PQS.”
- Corrective action and preventative action (CAPA) effectiveness, saying, “A comprehensive CAPA program has been identified as a strong indicator of a robust quality culture.”
- Process capability/performance, recognizing the importance of, “…statistical process control as a tool in understanding and managing variability in both product and processing for application and non-application products.”1
Encouraging this elevated quality culture across global networks can help CMOs and sponsors to embrace a common set of best practices with corresponding business benefits for both. While their business models may differ in the details, they need to embrace such a common culture of quality monitoring metrics, and collaborate to align their shared goals for product quality, patient outcomes, regulatory compliance and business success. The FDA has given the industry a map to its new quality frontier—with prescriptive advice for exploration—and getting on board now can only help sponsors and CMOs reach that new frontier sooner.
- “Draft Guidance for Industry: Request for Quality Metrics,” from Stakeholder Technical Webinar, U.S. Food and Drug Administration Center for Drug Evaluation and Research Center for Biologics Evaluation and Research, July 2015 http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/SmallBusiness%20Assistance/UCM456211.pdf
- “2016 Global life sciences outlook: Moving forward with cautious optimism,” Deloitte 2015. https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-2016-life-sciences-outlook.pdf
- Clarkston Consulting, “Life Sciences 2016 Contract Manufacturing Industry Trends,” 2015. http://clarkstonconsulting.com/wpcontent/uploads/2016/01/LS_CMO_Trends_2016.pdf
Justin Neway, Ph.D., is vice president and managing director, process production operations, and senior fellow, BIOVIA Science Council, at Dassault Systèmes. He has over 30 years of experience in biotechnology and pharmaceutical process development and manufacturing, and in the application of software solutions to operational issues and quality compliance. He can be reached at email@example.com.